Catching Up or Falling (Further) Behind? Migrant Disparities in Occupational Prestige Trajectories in Germany - Yannick Harksen July 1, 2022

Catching Up or Falling (Further) Behind? Migrant Disparities
in Occupational Prestige Trajectories in Germany

Yannick Harksen†
July 1, 2022
Humboldt-University of Berlin†

Introduction

Motivation i

               Figure 1: Migration to Germany: 1950 to 2020   1

Motivation ii

   Optimistic but Disadvantaged
     • Large share of migrants and their descendants in Germany (Destatis, 2020;
       Ellermann, 2021)

     • Germany not recognized as a migration society and patch-work integration
       policies (Adam, 2015; Green, 2013; Oltmer, 2016)
     • Disadvantaged in many spheres of society (Boeckh, 2018; Brenke, 2018; Kalter and
       Granato, 2018; Kogan, 2007; Seebaß and Siegert, 2011)

     • However: Immigrant Achievement Paradox (Salikutluk, 2016; Tjaden and Hunkler,
       2017; Van De Werfhorst and Van Tubergen, 2007)

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Motivation iii and aim of current study

   Issue: What has (not) been done?
     • Occupational prestige and development hereof as blind spot in research on
       migrant disparities
     • Occupational prestige is a distinct concept of social stratification
     • Previous research: mostly focused on first generation or no comparison to
       natives

   Aim: What has to be done?
     • Analyze differences in occupational prestige trajectories between migrants
       (1st and 2nd gen.) and natives
     • Thorough theoretical explanation taking into account structural
       characteristics as well
     • Multi-level growth curve models (SOEP v37, 1984-2020)                        3

Theoretical Framework

Explaining Migrant Disparities

                        Human Capital
      Migration
     Background

                         Demographic
                                                 First Occupation   Subsequent Mobility
                           Behavior

     Parental SES
                        Social Networks

                           Figure 2: Theoretical Mechanisms

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Analytical Strategy, Data and
Methods, Variables

Analytical Strategy, Data and Methods

   Data and Methods

     • SOEP v37 (1984-2020): Individuals between 14 and 64 years, max. 15 years of labor
       market experience, list-wise deletion
     • Multilevel Growth Curve Analysis with random intercepts and slopes:
     • yit = β0 + β1 Expit + β2 Exp2it + β3 MigBack + β4 MigBackxExpit + β5 MigBackxExp2it + γ0i +
       γ1i Expit + γ2i Exp2it + it

   Analytical Strategy
     • SOEP BIOJOB: Information on first job after finishing education
     • Incomplete information for individuals who joined the SOEP after joining labor
       market
     • Additional observation for these individuals                                                  5

Variables

   Dependent Variable Occupational Prestige: SIOPS (Treiman, 2013)
   Independent Variable Migration Background: 1. Natives, 2. 1st Gen. Migrants 3.
              2nd+ Gen. Migrants
   Explanatory Variables Labor Market Experience in years (Full+Part Time),
               Education (Low: ISCED 0-2; Medium: 3-4; High: 5-6), Parental SES
               (SIOPS Father; mean centered), Marital Status, Divorce, No. of
               Children, Occupational Closure of First Occupation (Index by Haupt
               et al. (2018); x100 and mean centered), Nace-Sector of First Job
      Controls Birth Cohort, East-/West-Germany, Part Time Employment,
               Unemployment Experience

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Results

Descriptive Results

                      7

Multivariable Results

                        8

Multivariable Results

                        9

Multivariable Results

                        10

Multivariable Results

                        11

Multivariable Results

                        12

Multivariable Results

                        13

Multivariable Results

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Conclusion

Conclusion

     • Male and Female 2nd gen. migrants are able to catch up to natives after
       about 15 years
           adjusting for explanatory variables does not change the trajectories
       profoundly
     • First gen. migrants experience u-shaped trajectory across the career
            Females hardly able to regain their initial occupational status; Males
       enabled to regain/surpass their initial occupational status
     • First gen. migrants with German educational credentials show almost similar
       trajectories than second gen. migrants
            ⇒ German educational credentials are highly important for migrants’
       intragenerational career mobility

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References

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  Germany”. In: Nationalism and Ethnic Politics 21.4, pp. 446–464.
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Brenke, Karl (2018). “Einkommensschwache Personen: die jüngere Entwicklung in
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Destatis (2020). Bevölkerung und Erwerbstätigkeit. Bevölkerung mit
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Kalter, Frank and Nadia Granato (2018). “Migration und ethnische Ungleichheit auf
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Seebaß, Katharina and Manuel Siegert (2011). Migranten am Arbeitsmarkt in
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